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Optimal Network-based Intervention in the Presence of Undetectable Viruses
Mina Youssef1, Caterina Scoglio2
1Network Dynamics and Simulation Science Laboratory, Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24061 USA ( myoussef@vbi.vt.edu ).
IEEE Communications Letters : a Publication of the IEEE Communications Society
|November 26, 2014
Summary
This study introduces an optimal control framework to slow virus spread in networks by reducing link weights. This approach improves upon existing models, revealing network structure
Area of Science:
- Network science
- Epidemiology
- Control theory
Background:
- Virus spread in networks is a significant concern.
- Existing epidemic models often rely on inaccurate assumptions.
- Understanding network structure's role in disease transmission is crucial.
Purpose of the Study:
- To present an optimal control framework for reducing virus propagation in networks.
- To develop an epidemic model that overcomes limitations of previous approaches.
- To analyze the impact of network topology on infection spread.
Main Methods:
- Modeling networks as undirected graphs with weighted links.
- Defining virus spread as a system state (infected nodes).
- Implementing optimal control via dynamical weight reduction.
Main Results:
- Demonstrated effective virus spread reduction through dynamical weight adjustment.
- Highlighted the influence of network structure on epidemic outcomes.
- Showcased the model's efficacy even with undetectable infected individuals.
Conclusions:
- Optimal control offers a viable strategy for mitigating network-based virus spread.
- The proposed epidemic model provides more accurate predictions.
- Network topology is a key factor in designing effective control interventions.
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